Task allocation in networks

Title: Task allocation in networks

Speaker: Francis Bloch (Université Paris 1 and PSE)

Abstract: We study dynamic task allocation when there is a fixed bipartite network associating workers to tasks. We analyze two approaches: centralized and decentralized. First, we study the optimal policy of a planner whose objective is to minimize the expected time of completion of all tasks. Second, we analyse a game played by workers who independently choose their tasks and are rewarded each time they complete a task. We characterize networks for which the planner’s and workers’ policies are simple. When policies are simple the planner prefers the workers to start with the hardest tasks, whereas workers always prefer to start with easier tasks. We show that the two policies only coincide when the bipartite network satisfies a strong symmetry condition. Differential rewards can be used to implement the planner’s optimal task allocation and we show that non- contingent rewards, which are independent of the set of remaining tasks, can only be implemented if there is no exclusive task.